This paper addresses the problem of detection and identification of sensor attacks in the presence of transient faults. We consider a system with multiple sensors measuring the same physical variable, where some sensors might be under attack and provide malicious values. We consider a setup, in which each sensor provides the controller with an interval of possible values for the true value. While approaches exist for detecting malicious sensor attacks, they are conservative in that they treat attacks and faults in the same way, thus neglecting the fact that sensors may provide faulty measurements at times due to temporary disturbances (e.g., a tunnel for GPS). To address this problem, we propose a transient fault model for each sensor and an algorithm designed to detect and identify attacks in the presence of transient faults. The fault model consists of three aspects: the size of the sensor's interval (1) and an upper bound on the number of errors (2) allowed in a given window size (3). Given such a model for each sensor, the algorithm uses pairwise inconsistencies between sensors to detect and identify attacks. In addition to the algorithm, we provide a framework for selecting a fault model for each sensor based on training data. Finally, we validate the algorithm's performance on real measurement data obtained from an unmanned ground vehicle.